class_docstr: This class implements the task-specific Lingvo ASR model of Qin et al. (2019).
  
  The estimator uses a pre-trained model provided by Qin et al., which is trained using the Lingvo library and the
  LibriSpeech dataset.
  
  | Paper link: http://proceedings.mlr.press/v97/qin19a.html, https://arxiv.org/abs/1902.08295
  
  .. warning:: In order to calculate loss gradients, this estimator requires a user-patched Lingvo module. A patched
               source file for the `lingvo.tasks.asr.decoder` module will be automatically applied. The original
               source file can be found in `<PYTHON_SITE_PACKAGES>/lingvo/tasks/asr/decoder.py` and will be patched as
               outlined in the following commit diff:
               https://github.com/yaq007/lingvo/commit/414e035b2c60372de732c9d67db14d1003be6dd6
  
  The patched `decoder_patched.py` can be found in `ART_DATA_PATH/lingvo/asr`.
  
  Note: Run `python -m site` to obtain a list of possible candidates where to find the `<PYTHON_SITE_PACKAGES` folder.
docstr: Return the shape of one input sample.
  
  :return: Shape of one input sample.
docstr_tok: ["Return","the","shape","of","one","input","sample",".",":","return",":","Shape","of","one","input","sample","."]
code: def input_shape(self) -> Tuple[int, ...]:
      """
      Return the shape of one input sample.
  
      :return: Shape of one input sample.
      """
      return self._input_shape
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import os
  import sys
  from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
  import numpy
  from art import config
  from art.estimators.speech_recognition.speech_recognizer import SpeechRecognizerMixin
  from art.estimators.tensorflow import TensorFlowV2Estimator
  from art.utils import get_file, make_directory
label_desc: Use image node_id 2 for calling the TensorFlowLingvoASR obj's underlying member method code with example usage: obj.input_shape() and returns: self